Radsam's Tuesdays AI litigation briefing for legal professionals, top-tier lawyers and honorable judges — June 23, 2026
- Pouya Shafabakhsh
- Jun 23
- 9 min read
This is an honest AI disclosure. This briefing is my, Pouya Shafabakhsh's analysis from the perspective of AI governance, risk, and compliance, and AI litigation. For the convenience of esteemed lawyers and busy C-suite executives, we have also created an AI-generated podcast, which provides a deep dive analysis for those who prefer listening over reading.
This is an honest AI disclosure. This briefing is my, Pouya Shafabakhsh’s analysis from the perspective of AI governance, risk, and compliance, and AI litigation. For the convenience of esteemed lawyers and busy C-suite executives, we have also created an AI-generated podcast, which provides a deep dive analysis for those who prefer listening over reading.
I. A Five-Figure Costs Order for AI-Fabricated Case Law
Canadian Lawyer reports that in Mazaheri v. Law Society of Ontario (2026 ONLSTH 112), a self-represented lawyer used a generative AI tool to prepare a factum, a supplementary factum, and affidavits, filed them without verifying the output, and cited cases that do not exist alongside real cases irrelevant to his argument. The Law Society Tribunal ordered him to bear $31,150 in costs — described as the largest such order by any Canadian court or tribunal to date for AI-fabricated citations.
AI GRC Specialist Analysis
The scale is the signal: earlier hallucination matters drew cautions or modest costs; this attaches a five-figure number, in Ontario, to the conduct. Ontario already codifies the underlying duty — Rule 4.06.1(2.1) of the Rules of Civil Procedure (added in 2024 via O. Reg. 384/24) requires a signed certification of the authenticity of every authority cited in a factum, and LSO Rule of Professional Conduct 3.1 requires competence. AI dilutes neither. The Tribunal did not sanction AI; it sanctioned filing without an independent check — a non-delegable duty. A documented, air-gapped verification of every authority before signing converts an invisible risk into a defensible control and yields a contemporaneous record a tribunal will credit. As the count of Canadian AI-citation decisions climbs steeply through 2026, the firms that institutionalize verification now are least likely to appear in next quarter's costs orders. Independent verification is the controllable variable between efficiency and a five-figure penalty.
II. AI Use in Arbitration Faces Red-Line Questions as a Canadian Court Annuls an Award
Law360 reports on an apparently novel Canadian decision setting aside an arbitral award for over-reliance on artificial intelligence. The Quebec Superior Court, in an April 22 ruling by Justice Martin F. Sheehan, annulled a Montreal arbitrator's award after finding that the doctrinal and jurisprudential references the arbitrator relied on were "non-existent and hallucinatory." The court did not ban AI for arbitrators but held that AI may assist, not drive, the decision.
AI GRC Specialist Analysis
This extends AI-integrity scrutiny beyond advocates to adjudicators. If a hallucinated authority can void an award, every participant acquires both an interest in verification and a potential ground to challenge an opaque, AI-assisted result. Parties often choose arbitration for finality; a decision like this shows how unverified AI can convert a closed matter into an annulment fight. For commercial, corporate, and M&A parties, the response is twofold: seek transparency about how an award was produced, and be prepared to support or contest the reasoning with independent analysis. The "red-line" framing is useful precisely because it is not a ban — it locates the risk in the degree and opacity of reliance, which is exactly what an independent review surfaces. As AI assistance becomes routine in adjudication, independent verification of the reasoning behind high-value awards becomes part of protecting the bargain the parties thought they struck.
III. The U.S. Judiciary Cites AI Deepfakes to Oppose Courtroom Cameras
Law360 reports that as two bipartisan bills to bring cameras into federal courtrooms advanced on June 18, 2026, the policymaking body for the federal judiciary continued to oppose them and expressly raised the issue of AI deepfakes — amid broader legislative attention including the NO FAKES Act of 2026 (S.4591), which would create a federal right over computer-generated digital replicas of an individual's voice or likeness.
AI GRC Specialist Analysis
The judiciary is naming deepfakes as a structural risk to the integrity of proceedings, not a peripheral concern — a framing that will ripple into evidentiary practice, where authenticity challenges to audio, video, and images are poised to multiply. For litigators in every practice area, prepare for authenticity to become contested terrain. When a single recording or image can decide a matter, the capacity to examine that exhibit forensically — and to explain the basis for concluding it is authentic or synthetic — becomes decisive. This is where the "liar's dividend" bites: the risk that genuine evidence is dismissed as AI-generated. Independent forensic examination of contested media, documented and reproducible under challenge, is moving from a niche service to a baseline capability. The judiciary's own concern is, in effect, an endorsement of independent verification: if the bench worries about fabricated media undermining trust, the answer is neutral, rigorous, technical authentication that the parties and the court can scrutinize.
IV. Bill C-36 Rewrites Canada's Private-Sector Privacy Law
Canadian Lawyer reports that Bill C-36, tabled June 15, 2026, would substantially replace the Personal Information Protection and Electronic Documents Act (PIPEDA) with a new Protecting Privacy and Consumer Data Act. The bill overhauls consent (express consent as default, with plain-language explanations), introduces deletion and data-mobility rights, and shifts private-sector privacy oversight to a Cabinet-appointed commission, with coming-into-force to be set by Order in Council.
AI GRC Specialist Analysis
For AI-driven legal and corporate practices, the relevance is direct. Stricter consent, deletion, and data-mobility duties land precisely where AI systems ingest, retain, and reuse personal information — including the client and matter data that flows through general-purpose AI tools. As the most significant federal privacy reform in over two decades moves through Parliament, ON–NY cross-border firms should map, now, where sensitive data traverses AI systems and who controls it. Data sovereignty — keeping the most sensitive files in an isolated, air-gapped environment rather than a public, multi-tenant model — shifts from best practice toward baseline diligence. The transition period created by an Order-in-Council coming-into-force is the window to get architecture right before the obligations bite, not after. Privacy reform and AI governance are converging into a single operational question: can you prove where your data went, and who could see it?
V. Lackluster AI Performance Tests Talent Retention and Client Satisfaction
Law.com reports on Thomson Reuters' 2026 Future of Professionals survey (1,816 professionals across legal, risk, compliance, tax and accounting; 736 legal; fielded March–April 2026). Among the findings: 24% of mid-career professionals would change jobs within two years if AI fails to deliver on their priorities, and 14% are considering leaving within twelve months; meanwhile 76% of corporate clients say AI-enabled quality improvements are very important or essential, but only 6% say they are receiving them from their providers.
AI GRC Specialist Analysis
The expectation-delivery gap is itself a risk surface. Clients now expect AI-enabled quality; firms that deploy AI without a verification layer risk producing work that is faster but not demonstrably better — and sometimes unverified. The retention angle compounds it: professionals stay where AI is deployed thoughtfully, not chaotically. The differentiator is not whether a firm uses AI, but whether it can demonstrate the output is sound. Independent verification turns "we used AI" into "we used AI under documented, defensible review" — the version that satisfies clients and withstands a tribunal's scrutiny. For leadership, closing the 76%-to-6% gap is both a client-retention strategy and a risk-management one; the same verification discipline serves both. Quality you can prove is the product clients are actually asking for.
VI. Thomson Reuters: AI Adoption Among Professionals Is "Slow and Chaotic"
Artificial Lawyer reports on a Thomson Reuters survey finding the current state of professional AI adoption often slow and chaotic: roughly a third of firms report no significant AI plan, the largest cohort (40%) are experimenting without a structured approach, and fewer than one in five organizations measure AI's return on investment, even as a large majority acknowledge AI's transformative impact.
AI GRC Specialist Analysis
Adoption without governance is the precise condition that generates professional-conduct risk. The same disorder that produces "chaotic" rollouts produces unverified filings, undocumented prompt trails, and inconsistent quality control — the raw material of this year's sanctions and costs orders. The survey reframes a maturity gap as a liability profile. Firms turning AI into durable advantage treat governance as a precondition rather than an afterthought: defined tools, defined data boundaries, and an independent verification step before anything is filed or published. "Slow and chaotic" is not neutral — in a year of escalating AI-citation penalties across Ontario, Quebec, and the U.S. courts, it is an exposure that compounds. An external, independent verification partner is one efficient way to impose order: a consistent standard, a reproducible record, and an accountability boundary that ad-hoc internal use rarely achieves. An AI strategy without a verification layer is not a strategy; it is unmanaged risk.
VII. NYC Bar AI Conference: Teaching AI in Law Schools and Tracking Global Regulation
Law.com reports that at the New York City Bar Artificial Intelligence Conference, experts discussed how to responsibly integrate AI curriculum into legal education and how to navigate the current patchwork of international AI regulation.
AI GRC Specialist Analysis
The conference reflects a profession institutionalizing AI competence — and competence, once expected, becomes the benchmark against which conduct is later judged. For New York practitioners, the regulatory "patchwork" is the operative risk: 22 NYCRR Part 161's certification duty (in force June 1, 2026), judge-specific disclosure part-rules, and cross-border obligations rarely align cleanly. A practitioner operating across Ontario and New York must satisfy the strictest applicable rule in each matter. The efficient answer is a single, documented verification standard — built to the most demanding requirement — so process does not have to be re-engineered case by case. Teaching AI in law schools will, over time, raise the floor of expected competence; firms that already operate to a defensible standard will simply be ahead of it. Education raises expectations; verification meets them.
VIII. BARBRI Acquires Lega, Signaling a Pivot Toward Experiential AI Training
Law.com reports that legal-education company BARBRI has acquired Lega — founded in 2023 by Christian Lang — to deliver experiential AI training (workshops, simulations, and hackathons) at scale to law students, lawyers, and firms. Lang will join BARBRI as Head of Innovation; financial terms were not disclosed.
AI GRC Specialist Analysis
The deal is a market signal worth reading. Capital and consolidation are flowing toward practical AI fluency for lawyers — a sign the profession expects AI skill to become table stakes. But fluency in using AI is not the same as competence in verifying it, and the governance question follows close behind the skills question. The firms that pair adoption and training with independent verification will convert AI literacy into defensible work product; those that treat training as the finish line risk producing confident, faster, but unverified output. Skill-building and verification are complements, not substitutes: one increases throughput, the other ensures the throughput holds up in front of a court or regulator. As legal-AI education scales, the demand for an independent check on what that education produces scales with it.
IX. The Legal Profession's AI Tightrope
Artificial Lawyer, in a piece by James Tuke of the AI Futures Forum, argues that the profession is walking a dangerous AI tightrope: automating the routine "grunt work" that once trained junior lawyers risks hollowing out the talent pipeline, making the real challenge ahead cultural and economic, not merely technological.
AI GRC Specialist Analysis
The tightrope framing maps directly onto risk. Over-delegation to AI — stripping out the human checkpoints where judgment is built — is exactly what produces unverified filings and, over time, a thinning bench of lawyers able to catch the errors. Governance is the balancing pole: keep AI on the efficiency side of the line and humans on the verification and judgment side. The economic pressure to automate is real, but so is the professional-conduct exposure when automation outruns oversight. An independent verification layer reinforces that division of labour — capturing AI's speed on routine work while preserving the human accountability the courts now demand at the point of signing and filing. The firms that navigate the tightrope will be those that treat verification not as friction, but as the safety line that lets them move faster with confidence.
X. Shalini Konanur Elected Treasurer of the Law Society of Ontario
Law360 Canada reports that Shalini Konanur — executive director and senior lawyer at the South Asian Legal Clinic of Ontario, and a Law Society Tribunal adjudicator — has been elected Treasurer of the Law Society of Ontario for the 2026–27 term, effective the June 25 Convocation, becoming the first racialized woman elected to the role.
AI GRC Specialist Analysis
Regulator leadership matters for AI-GRC because the Treasurer helps set the tone on competence, technology, and professional conduct. With Ontario tribunals already imposing five-figure costs for AI-fabricated citations (see item I) and Rule 4.06.1(2.1) now requiring certification of the authenticity of every authority, the direction of travel is toward firmer expectations on verification and candour. Konanur's own background — running a clinic and adjudicating at the Law Society Tribunal — sits at the intersection of access to justice and professional discipline, both of which AI risk now touches. For practitioners, the takeaway is to read regulator transitions as a cue to get ahead of the standard: document independent verification of AI-assisted work now, rather than after a costs motion frames the question. Anticipating the regulator's direction is cheaper than reacting to it.
If you are a managing partner, general counsel, C-suite executive, or a solo practitioner lawyer of high-stake litigation including IP, patent, class action, corporate, and M&A within Ontario and New York corridor, and would like to protect your upcoming court by being 100% aligned with Law Society of Ontario, New York State Bar, such as 22 NYCRR Part 161, ORAG 384/24, LSO By-Law 4, and federal acts such as US Cloud Act, PIPEDA, for AI mandated requirements, we would invite you to fill out our assessment form as Radsam's Sovereign Sanctuary Vault is lined up by the highest sensitive files. Accepting the new file is selective and depends on the capacity and case. One of our team will review your information and a judicial forensic AI auditor from Radsam's Toronto office will contact you in two business days.
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Author: Pouya Shafabakhsh Co-Founder, CAIO & Principal Forensic AI Auditor, Radsam Academy of AI Sovereign Governance. The Architect of North America's: Judicial Forensic AI Audit Standards, AI Governance, Risks & Compliance Standards, Air-Gapped Sovereign Sanctuary AI Audit System.
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